What is the Google Cloud ADK?

The Agent Development Kit (ADK) is an open-source Python framework from Google designed to build production-ready AI agents in under 100 lines of code.

How does this skill help with deployment?

It provides standardized scaffolding and commands for deploying agents to Vertex AI Agent Engine, Cloud Run, and Google Kubernetes Engine (GKE).

What triggers this skill in Claude Code?

The skill activates automatically when you use phrases like 'adk', 'agent development kit', 'multi-agent', 'agent starter pack', or 'build agent'.

Can I build multi-agent systems with this skill?

Yes, it supports hierarchical coordination, parallel execution, and specialized sub-agent patterns for complex project orchestration.

Does it support RAG (Retrieval-Augmented Generation)?

Yes, it includes native integrations for Vertex AI Search and Vector Search to build agents that retrieve and reason over private data.

Google Cloud AI Agent Master

Name: Google Cloud AI Agent Master
Author: BbgnsurfTech

byBbgnsurfTech

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クラウドインフラストラクチャ

Simplifies the development and deployment of production-grade AI agents using the Google Cloud Agent Development Kit (ADK).

概要

This skill provides comprehensive guidance for building, orchestrating, and deploying containerized AI agents using Google's official ADK and Agent Starter Pack. It enables developers to implement multi-agent systems, RAG patterns, and production-ready CI/CD pipelines on platforms like Vertex AI, Cloud Run, and GKE. It is particularly useful for engineering teams moving from prototypes to scalable, enterprise-grade agentic workflows with built-in monitoring, evaluation, and security best practices.

主な機能

Multi-agent system orchestration and coordination
Built-in evaluation and observability with Cloud Trace
3 GitHub stars
Production-ready deployment to Cloud Run, GKE, and Agent Engine
Automated RAG (Retrieval-Augmented Generation) implementation
Integrated CI/CD pipeline scaffolding with Agent Starter Pack

ユースケース

Setting up automated evaluation pipelines for LLM performance monitoring
Building a multi-agent coding system using CrewAI or LangGraph templates
Deploying a containerized RAG agent for document retrieval on Vertex AI

概要

主な機能

Multi-agent system orchestration and coordination
Built-in evaluation and observability with Cloud Trace
3 GitHub stars
Production-ready deployment to Cloud Run, GKE, and Agent Engine
Automated RAG (Retrieval-Augmented Generation) implementation
Integrated CI/CD pipeline scaffolding with Agent Starter Pack

ユースケース

Setting up automated evaluation pipelines for LLM performance monitoring
Building a multi-agent coding system using CrewAI or LangGraph templates
Deploying a containerized RAG agent for document retrieval on Vertex AI